Real-time decentralized cooperative robust trajectory planning for multiple UCAVs air-to-ground target attack

Abstract

Planning cooperative trajectories in real time is of great importance for multiple unmanned combat aerial vehicles (multi-UCAV) in performing autonomous time-critical cooperative air-to-ground target attack missions. The models of the vehicle, constraints, and a multi-criteria objective function are set up, and then the problem is formulated as a decentralized cooperative receding horizon optimal control problem. An elaborate framework for provable effective decentralized cooperative trajectory planning in two-degree-of-freedom decentralized receding horizon control is presented to provide the robustness and adaptivity for trajectory planning in dynamic and uncertain environments. Furthermore, a two-stage iterative optimization algorithm is developed to solve the problem. The novel algorithm integrates the differential flatness theory to generate trajectories, and the coordination variable-based strategy to coordinate the arrival time of multi-UCAV online, which can improve the computational efficiency and achieve the cooperative objective. The results of numerical simulations show that the proposed approach is feasible and well suited for the real-time implementation in dynamic and uncertain environment.